Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userMultigranular modeling of ionic liquids
67
0
0.0
(
0
)
Ask ChatGPT about the research
No Arabic abstract
Ionic liquids are a special category of molten salts with melting points near ambient temperatures or by convention below 100 C. Owing to their numerous valuable physicochemical properties as bulk liquids, solvents, at surfaces and in confined environments, ILs have attracted increasing attention in both academic and industrial communities in a variety of application areas involving physics, chemistry, material science and engineering. Due to their nearly limitless number of combinations of cation and anion pairs and mixtures with cosolvents, a molecular level understanding of their hierarchical structures and dynamics, requiring strategies to connect several length and time scales, is of crucial significance for rational design of ILs with desired properties, and thereafter refining their functional performance in applications. As an invaluable compliment to experiments from synthesis to characterization, computational modelling and simulations have significantly increased our understanding on how physicochemical and structural properties of ILs can be controlled by their underlying chemical and molecular structures. In this chapter, we will give examples from our own modelling work based on selected IL systems, with focus on imidazolium based and tetraalkylphosphonium orthoborate ILs, studied at several spatiotemporal scales in different environments and with particular attention to applications of high technological interest.
rate research
Read More
Ionic Liquids (ILs) are organic molten salts characterized by the total absence of solvent. They show remarkable properties: low vapor pressure, high ionic conductivity, high chemical, thermal and electrochemical stability. These electrolytes meet therefore key criteria for the development of safe energy storage systems. Due to a competition between electrostatic and van der Walls interactions, ILs show an uncommon property for neat bulk liquids: they self-organize in transient nanometric domains. In ILs-based electrochemical devices, this fluctuating nano-segregation acts as energy barriers to the long range diffusional processes and hence to the ionic conductivity. Here, we show how the ionic conductivity of ILs can be increased by more than one order of magnitude by exploiting one dimensional (1D) confinement effects in macroscopically oriented carbon nanotube (CNT) membranes. We identify 1D CNT membranes as promising separators for high instant power batteries.
Ionic liquids are promising candidates for electrolytes in energy-storage systems. We demonstrate that mixing two ionic liquids allows to precisely tune their physical properties, like the dc conductivity. Moreover, these mixtures enable the gradual modification of the fragility parameter, which is believed to be a measure of the complexity of the energy landscape in supercooled liquids. The physical origin of this index is still under debate; therefore, mixing ionic liquids can provide further insights. From the chemical point of view, tuning ionic liquids via mixing is an easy and thus an economic way. For this study, we performed detailed investigations by broadband dielectric spectroscopy and differential scanning calorimetry on two mixing series of ionic liquids. One series combines an imidazole based with a pyridine based ionic liquid and the other two different anions in an imidazole based ionic liquid. The analysis of the glass-transition temperatures and the thorough evaluations of the measured dielectric permittivity and conductivity spectra reveal that the dynamics in mixtures of ionic liquids are well defined by the fractions of their parent compounds.
It is well-known that room temperature ionic liquids (RTILs) often adopt a charge-separated layered structure, i.e., with alternating cation- and anion-rich layers, at electrified interfaces. However, the dynamic response of the layered structure to temporal variations in applied potential is not well understood. We used in situ, real-time X-ray reflectivity (XR) to study the potential-dependent electric double layer (EDL) structure of an imidazolium-based RTIL on charged epitaxial graphene during potential cycling as a function of temperature. The results suggest that the graphene-RTIL interfacial structure is bistable in which the EDL structure at any intermediate potential can be described by the combination of two extreme-potential structures whose proportions vary depending on the polarity and magnitude of the applied potential. This picture is supported by the EDL structures obtained by fully atomistic molecular dynamics (MD) simulations at various static potentials. The potential-driven transition between the two structures is characterized by an increasing width but with an approximately fixed hysteresis magnitude as a function of temperature. The results are consistent with the coexistence of distinct anion and cation adsorbed structures separated by an energy barrier (~0.15 eV).
Room-temperature ionic liquids (RTILs) stand out among molecular liquids for their rich physicochemical characteristics, including structural and dynamic heterogeneity. The significance of electrostatic interactions in RTILs results in long characteristic length- and timescales, and has motivated the development of a number of coarse-grained (CG) simulation models. In this study, we aim to better understand the connection between certain CG parametrization strategies and the dynamical properties and transferability of the resulting models. We systematically compare five CG models: a model largely parametrized from experimental thermodynamic observables; a refinement of this model to increase its structural accuracy; and three models that reproduce a given set of structural distribution functions by construction, with varying intramolecular parametrizations and reference temperatures. All five CG models display limited structural transferability over temperature, and also result in various effective dynamical speedup factors, relative to a reference atomistic model. On the other hand, the structure-based CG models tend to result in more consistent cation-anion relative diffusion than the thermodynamic-based models, for a single thermodynamic state point. By linking short- and long-timescale dynamical behaviors, we demonstrate that the varying dynamical properties of the different coarse-grained models can be largely collapsed onto a single curve, which provides evidence for a route to constructing dynamically-consistent CG models of RTILs.
A first-principle multiscale modeling approach is presented, which is derived from the solution of the Ornstein-Zernike equation for the coarse-grained representation of polymer liquids. The approach is analytical, and for this reason is transferable. It is here applied to determine the structure of several polymeric systems, which have different parameter values, such as molecular length, monomeric structure, local flexibility, and thermodynamic conditions. When the pair distribution function obtained from this procedure is compared with the results from a full atomistic simulation, it shows quantitative agreement. Moreover, the multiscale procedure accurately captures both large and local scale properties while remaining computationally advantageous.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
